Radio Receiver in a Wireless Communications System

ABSTRACT

Techniques are described for optimizing processing facilities of a receiver in a wireless communication environment, taking into consideration processing performance set against the computing resources and/or power consumption required to obtain the processing performance. An embodiment of a radio receiver is described that includes a channel equalization means arranged to receive digital samples of an incoming signal and to generate an equalized output, said channel equalization means including means for processing said digital samples in accordance with an equalizer algorithm utilizing a set of equalizer parameters. The receiver can include means for estimating at least one parameter of a channel over which the signal has been received, and means for selecting at least one of said equalizer parameters based on at least one of said estimated channel parameters. Related methods, algorithms, and computer program products are also described.

This application claims priority to GB Application No.: 0721424.0 filed31 Oct. 2007, the contents of which are incorporated herein by referencein its entirety.

The present invention relates to a radio receiver in a wirelesscommunications system, and to a method of processing radio signals.

The transmission of radio signals carrying data in modern wirelesscommunications can be realized based on a number of differentcommunications systems, often specified by a standard. There areincreasing requirements for devices which are able to operate to supportmore than one of these wireless communications systems. Mobile radioreceiver devices include analog radio frequency (RF)/intermediatefrequency (IF) stages, which are arranged to receive and transmitwireless signals via one or more antennas. The output of the RF/IFstages is typically converted to baseband, where an Analog-to-DigitalConverter (ADC) converts incoming analog signals to digital samples,which are then processed for signal detection and decoding of the datain the form of reliability values. The ADC may alternatively operatedirectly at IF, in which case the conversion to baseband is performed inthe digital domain. A number of different types of front end processingof the digital samples are known to implement signal detection,including rake receiver processing and channel equalisation processing.

In Code Division Multiple Access (CDMA) wireless systems, differentphysical channels are multiplexed in the code domain using separatespreading sequences. In the case of orthogonal spreading codewords, theoriginal data symbols can then be effectively separated at the receiverby despreading.

In a Wideband CDMA (WCDMA) cellular system, downlink code multiplexingis performed using Orthogonal Variable Spreading Factor (OVSF) codes.However, the OVSF codewords are orthogonal to each other only under thecondition of perfect time alignment. In the presence of multipathpropagation, the code orthogonality is lost, and the operation ofdespreading is affected by Multiple Access Interference (MAI).

CDMA mobile radio receivers conventionally employ a rake processor whichrelies on the correlation properties of the spreading sequences. A rakeprocessor is described for example in J. G. Proakis, “DigitalCommunication”, New York, McGraw-Hill, 1995. This type of receiver issubject to performance degradation in the presence of code correlation,if the MAI between code-multiplexed transmission is comparable to theother sources of noise and interference. Under these conditions, aperformance advantage may be achieved by attempting to restore theorthogonality between the codes before despreading. The sub-optimalityof conventional 3GPP receivers based on rake processing causes asignificant performance penalty, especially for downlink data ratesincreasing from the 384 kbps for WCDMA Release 99 to High Speed DownlinkPacket Access (HDSPA) rates of several Mbps. When the code orthogonalityis destroyed by multipath, an effective approach is to use channelequalisation instead of rake processing.

Channel equalisation techniques have been widely employed over the lastdecades for combating intersymbol interference on frequency selectivetransmission channels. Channel equalization techniques are described inJ. G. Proakis, “Digital Communication”, New York, McGraw-Hill, 1995, andS. Benedetto, E. Biglieri, and V. Castellani, “Digital TransmissionTheory”, Englewood Cliffs, N.J., Prentice-Hall, 1987. Channel equalisershave recently found application in receivers for Time Division MultipleAccess (TDMA) and Code Division Multiple Access (CDMA) mobile wirelesssystems. An example of application of channel equalisation to a CDMAcellular system is described in A. Klein “Data Detection AlgorithmsSpecially Designed for the Downlink of CDMA Mobile Radio Systems”, inProceedings of IEEE Vehicular Technology Conference, vol. 1, Phoenix,Ariz., May 1997, pp. 203-207. In particular in synchronous CDMA cellularsystems, as in the case of the forward link of the 3GPP WCDMA standard,chip level equalisation allows to significantly improve the performanceover conventional rake receivers, at the cost of an increasedimplementation complexity. This advantage is especially important forhigh rate data transmission, as in 3GPP high speed downlink packetaccess (HSDPA).

It is an aim of the present invention to optimise the processingfacilities of a receiver in a wireless communication environment, inparticular taking into account processing performance set against thecomputing resources and/or power consumption required to obtain thatprocessing performance.

According to an aspect of the present invention there is provided aradio receiver for a wireless communication system comprising: channelequalisation means arranged to receive digital samples of an incomingsignal and to generate an equalised output, said channel equalisationmeans comprising means for processing said digital samples in accordancewith an equaliser algorithm utilising a set of equaliser parameters;means for estimating at least one parameter of a channel over which thesignal has been received; and means for selecting at least one of saidequaliser parameters based on at least one of said estimated channelparameters.

Another aspect of the invention provides a method of processing radiocommunication signals in a radio receiver, the method comprising:receiving digital samples of an incoming radio communication signal andprocessing those samples in accordance with an equaliser algorithmutilising a set of equaliser parameters to generate an equalised output;estimating at least one parameter of a channel over which the incomingsignal has been transmitted; and selecting at least one of saidequaliser parameters based on at least one of said estimated channelparameters.

A computer program product is also provided which implements the methoddefined above when executed on a processor. In this case, the processorcan constitute the same processing means as the one that executes theequaliser algorithms themselves. That is, the program for selecting oneof a plurality of equaliser parameters can be executed by the sameprocessor that executes the algorithms themselves to implement anequaliser function.

The inventors have realised that the extent to which channelequalisation can provide an optimised trade-off between superiorperformance and use of the available processing resources and/or powerconsumption is dependent on certain channel conditions. Moreparticularly, the inventors have appreciated that the particularequalisation parameters which is used to implement the channelequalisation can provide different benefits in dependence on certainchannel conditions.

In this context, the word channel is used to denote the communicationpath of the radio signals. According to the communication system used,channels can be defined by time, code or frequency, as is well known inthe art. The quality of particular channels is affected by conditionsrelated to the propagation environment, the cellular layout and otherconditions in the wireless communications system.

For a better understanding of the present invention and to show how thesame may be carried into effect, reference will now be made by way ofexample to the accompanying drawings in which:

FIG. 1 is a schematic block diagram of a wireless communications device;

FIG. 2 is a block diagram showing selection between rake receiverprocessing and equaliser processing;

FIG. 3 is a schematic block diagram of processing functions;

FIG. 4 is a schematic diagram of a sequence of steps for selecting aprocessing function;

FIG. 5 is a schematic block diagram for the selection of a set ofequaliser parameters; and

FIG. 6 is a schematic block diagram for the selection of the equaliseralgorithm.

FIG. 1 is a schematic block diagram of a device for transmitting andreceiving signals in a wireless communications system. Such a device canbe implemented in a number of different ways, but in accordance withFIG. 1 a series of RF/IF stages 32 is arranged to receive and transmitwireless signals (TX, RX) via one or more antennas 20. The embodimentsof the present invention discussed herein are principally concerned withreceiving wireless signals, and so that transmit signals will not bementioned further. The received signal at the output of the RF/IF stagesis typically converted to baseband, where an ADC converts the analogsignal into digital samples. The block 32 of FIG. 1 includes componentsfor processing the received radio signals and providing digital signalsamples r(k). This can be achieved in different ways, which are known inthe art and which are not discussed further herein.

The samples r(k) are supplied to a data transfer engine 30 whichcommunicates with a processor 22, an instruction memory 24 and a datamemory 26. The processor 22 is responsible for processing the samplesr(k). The processor 22 can execute a number of different functions whichare held in an instruction memory 24 in the form of code sequences. Thisprovides a so-called soft modem which has a number of advantagesdiscussed further herein.

FIG. 2 and FIG. 3 are schematic block diagrams which illustrate someamong a number of different functions that are executed by the processor22. A first function denoted by block 10 is referred to as estimation ofchannel parameters. This function estimates a number of differentparameters related to the communication channels over which the radiosignals are transmitted in the wireless communication system. Thefunction 10 provides at time k the outputs γ_(n)(k), n=1, . . . , N_(C),where N_(C) denotes the number of estimated channel parameters, thatrepresent a set of channel parameters derived from the received signalsamples r(k). The estimated channel parameters γ_(n)(k) can be used fora number of different purposes. As illustrated in FIG. 2 and FIG. 3,they are supplied to a Selection of Rake/Equaliser Receiver function 12which determines whether to process the received samples using a rakereceiver or an equaliser receiver. The rake receiver or equaliserreceiver is implemented by the processor 22 executing the appropriatecode sequence from the instruction memory 24.

The parameters γ_(n)(k) are further supplied to a Selection of EqualiserAlgorithm function 18 which is used in the event that an equaliserreceiver 16 is selected. If used, the function 18 selects a particularalgorithm for implementing the equaliser receiver 16 based on thechannel parameters which have been estimated. The algorithm is suppliedto the channel equaliser as denoted diagrammatically by input 17. Inpractice of course this will be implemented by the appropriate algorithmbeing selected as a code sequence from the instruction memory.

The channel parameters γ_(n)(k) are also supplied to a Selection ofEqualiser Parameters function 14. The equaliser parameter selectionfunction 14 is used in the event that an equaliser receiver is selected(as denoted by block 16) and controls parameters used for implementingthe equaliser receiver, these parameters being denoted θ_(n)(k), n=1, .. . , N_(E), where N_(E) denotes the number of relevant equaliserparameters.

The use of the estimated channel parameters to control the selection ofa rake receiver or equaliser receiver (function 12) will now bediscussed in more detail. FIG. 2 illustrates the concept in schematicform. The digital samples r(k) are supplied to a switch 4 which has aninput 5 receiving the command signal for the selection of rake receiveror equaliser processing from the function 12. In accordance with thissignal, the switch 4 selects a processing path 6 via a rake receiver 7,or a processing path 8 via an equaliser 9. As is known in the art, therake receiver includes a set of rake fingers 7 a, 7 b, . . . , for eachchannel transmitted on a separate channelization code. Each finger isassociated with a single descrambler/despreader 9 and a weightingfunction 11, and the set of fingers relative to each channel areassociated to an adder 13 providing a processed output on output path15. As the operation of a rake receiver is well understood to a personskilled in the art, its function will not further be described here.

The equaliser receiver 19 comprises a chip level equaliser 16 and aplurality of descramblers/depreaders 21 a, 21 b, . . . for each channeltransmitted on a separate channelization code. The outputs of thedescramblers/despreaders are supplied along output path 23. An outputswitch 25 provides processed outputs on lines 27 to subsequent decodingfunctions. The switch 25 is (like the switch 4) controlled by controlinput 5 which receives the command signal for the selection of rakereceiver or equaliser from the function 12.

While FIG. 2 illustrates the concept of processing function selection,it will readily be appreciated that in the embodiment of the inventionillustrated in FIG. 1 it is not possible to identify different physicalpaths (6, 8, 15, 23). Instead, selection is made by downloadingdifferent code sequences dependent on whether a rake receiver functionor equaliser receiver function is to be executed by the processor 22.

In such a software implementation of the receiver, where only eitherrake or equaliser processing is performed at any given time, the aboveapproach also provides an overall reduction of computational complexitywith respect to a conventional receiver implementing a channel equaliserin hardware. In this respect conventional modems based on a hardwareimplementation are forced to the choice between a design dictated by themaximum data rate requirements and the instantiation of multiplealgorithms as separate areas of silicon. These solutions imply higherimplementation costs, size and/or power consumption and any compromisewould inevitably penalise performance. On the other hand, the proposedsolution allows to reduce complexity, size and cost by reusing a commonplatform to adaptively select the optimum set of signal processingfunctions capable of maximising performance and minimise powerconsumption.

Reference will now be made to FIG. 4 to describe a method of selecting aprocessing function based on the estimation of particular channelparameters. The inventors have found that it is advantageous to applythe selection criteria by examining different channel parameters in acertain sequence (as illustrated in FIG. 4 and described below). It willreadily be appreciated however that other appropriate sequences may alsobe utilised.

Step S1 produces an estimate of the degree of non-stationarity of thechannel, related to mobility of the user of the transmission channel,given for example by an estimate of the Doppler spread or the maximumDoppler frequency or by an estimate of the relative speed of the mobileterminal. These estimators are known in the art and so the manner inwhich it is estimated is not discussed further herein. Examples aredescribed in G. L. Stuber, “Principles of Mobile Communications”,Norwell, Mass., Kluwer, 1996, A. Sampath and J. M. Holtzman, “Estimationof Maximum Doppler Frequency for Handoff Decisions”, in Proceedings ofIEEE Vehicular Technology Conference, Secaucus, N.J., May 1993, pp.859-862, C. Tepedelenlioglu, A. Abdi, G. B. Giannakis, and M. Kaveh,“Estimation of Doppler spread and Signal Strength in MobileCommunications with Applications to Handoff and Adaptive Transmission”,Wireless Communications and Mobile Computing, vol. 1, no. 2, pp.221-242, March 2001, and references therein. The receiver can bedesigned to use equaliser processing for relatively low time-varyingchannels, and to switch to rake processing for fast time-varyingchannels, where the switching threshold should depend on the desiredtrade-off between equaliser complexity and receiver performance ADoppler comparison step S2 compares a Doppler estimation signal γ₁ witha suitable threshold Th_(D). If γ₁ exceeds the threshold Th_(D), thestep selects rake receiver processing. If the Doppler estimation signalγ₁ does not exceed the threshold Th_(D), the comparison produces anegative answer, and the selection process continues with anout-of-window energy comparison step.

The out-of-window energy estimation S3 provides an estimate of thechannel energy outside the time window used for equaliser channelestimation. An example is described in C. Luschi, M. Sandell. P.Strauch, and R.-H. Yan, “Adaptive Channel Memory Truncation for DigitalMobile Communications”, in Proceedings of IEEE International Workshop onIntelligent Signal Processing and Communication Systems, Melbourne,Australia, November 1998, pp. 665-669. Equaliser processing is selectedonly when a significant percentage of the channel energy is captured bythe channel estimation window—which will not happen in the case of veryhigh delay spread). To this end, the out-of-window energy γ₂ is comparedwith a threshold Th_(W). If γ₂ is greater than the threshold Th_(W), thestep selects rake receiver processing. If the out-of-window energy γ₂ isnot greater than Th_(W), to the selection process continues with asingle-ray channel detection step.

A delay spread estimation S5 generates an output γ₃, given for exampleby an estimate of the root mean square (rms) delay spread. An example ofdelay spread estimation is given in H. Arslan and T. Yucek, “DelaySpread Estimation for Wireless Communication System”, in Proceedings ofIEEE International Symposium on Computers and Communication,Kemer-Antalya, Turkey, June-July 2003, pp. 282-287. The parameter γ₃ issupplied to the single-ray channel detection step S6 to determine if thetransmission channel can be considered to result from a singlepropagation path (multipath absent). In case of single-path propagation,the step selects rake receiver processing.

More generally identification of the conditions of very high delayspread (long channel impulse response) and zero delay spread (single raychannel impulse response) can be used to switch the receiver to rakereceiver processing. The term “channel length” is often used in the artto denote the temporal duration of the channel impulse response, whichis related to the channel delay spread.

In the event of non single-ray channel, the process passes to anestimate of channel characteristics from the location of the channelzeros in the z-plane (S7). Examples of how this is done are given in Y.Bistritz, “Zero Location with Respect to the Unit Circle ofDiscrete-Time Linear System Polynomials”, Proceedings of the IEEE, vol.72, no. 9, pp. 1131-1142, September 1984, and references therein. Thereceiver may be designed to switch to rake processing in the presence oflocations of the zeros that identify channel characteristics that arecritical for the operation of the equaliser—as in the case of linearequalisation with channel zeros close to the unit circle of the z-plane,or for fractionally-spaced equalisation or, more generally receivediversity equalisation (multiple receive antennas or multiplesubchannels obtained by oversampling) with common zeros among theequaliser subchannels. The estimate of the channel zeros location γ₄ issupplied to a critical zeros location detector step S8, which selectsrake receiver processing in the presence of the locations of zeros whichwould be critical for operation of an equaliser. In case of non-criticalchannel characteristics, the selection process continues with a cellgeometry comparison step.

A cell geometry estimation block provides an estimate γ₅ of the ratiobetween received intracell power and noise-plus-intercell interferencepower (or its inverse), or an estimate of the ratio between totalreceived power and noise-plus-intercell interference power (or itsinverse). An example of a cell geometry estimation technique that can beused is described in our copending application [PWF Ref. 316036 GB].Alternatively, any known technique for estimating signal to disturbanceratios on an incoming radio signal can be used, where disturbance isinterference or noise or both. An example of signal to disturbance ratioestimation for a wireless cellular system is given in M. Turkboylari andG. L. Stuber, “An Efficient Algorithm for Estimating theSignal-to-interference Ratio in TDMA Cellular Systems”, IEEETransactions on Communications, vol. 46, no. 6, pp. 728-731, June 1998.As a further alternative, an estimate of the signal to disturbance ratioγ₆ of the estimated channel response can be used, or any otherindication of the quality of the available channel estimate.

In addition to switching between the rake and equaliser, in the casethat the equaliser 16 has been selected the channel parameters estimatedby the channel parameter estimation function 10 can be used to selectthe parameters θ_(n), n=, . . . , N_(E) for the implementation of theequaliser 16.

FIG. 5 is a schematic block diagram for the selection of a set ofequaliser parameters within the equaliser parameter selection function14.

The time window W for estimation of the channel impulse response in theequaliser can be selected on the basis of estimates of the channelout-of window energy γ₂ and/or of the channel delay spread γ₃ (block 14a of FIG. 5). This selection mat also depend on an estimate γ₅ of theinput signal-to-disturbance ratio or the cell geometry, and/or on anestimate γ₆ of the signal-to-disturbance ratio for the estimated channelcoefficients.

The memory of an appropriate filter for estimation of the channelimpulse response (block 14 b of FIG. 5) and the frequency of update ofthe estimated channel impulse response (block 14 c of FIG. 5) can beselected on the basis of an estimate of the degree of channelnon-stationarity or temporal selectivity, for example through anestimate of the channel Doppler spread γ₁. The selection of the channelestimation filter could also be based on an estimate γ₅ of the inputsignal-to-disturbance ratio or the cell geometry, and/or on an estimateγ₆ of the signal-to-disturbance ratio of the estimated channel response.

At intermediate to low signal to noise-plus-interference ratios, thetotal channel estimation error can be reduced by setting to zero theestimated channel coefficients with amplitude lower than a suitablethreshold. The value of this threshold can be selected based on anestimate γ₅ of the input signal-to-disturbance ratio or the cellgeometry, and/or on an estimate γ₆ of the signal-to-disturbance ratiofor the estimated channel coefficients (block 14 d of FIG. 5).

The memory of appropriate filters for estimation of the input noisevariance σ², for example in the case of MMSE equalisation, can be madeadaptive in the presence on non-stationary input noise by measuring thedegree of non-stationarity of the input disturbance γ₇ (for instance,the time interval over which the noise is approximately constant) (block14 c of FIG. 5). On a completely different basis, the filtering maydepend on the periodicity with which it is convenient to collectobservations on the input noise—this in turn may be motivated simply bythe need to reduce the implementation complexity in specific operatingconditions or under critical processing requirements.

The number of equaliser coefficients (i.e., the equaliser time span) canbe selected for example on the basis of estimates of the channel out-ofwindow energy γ₂ and/or of the channel length or the channel delayspread γ₃ and on an estimate of the position of the channel zeros in thez-plane γ₄ (block 14 f of FIG. 5).

The number of feedforward and feedback equaliser coefficients in thecase of decision feedback equalisation can similarly be based onestimates of the channel out-of-window energy γ₂ and/or of the channellength (or the channel delay spread) γ₃ and the position of the channelzeros in the z-plane γ₄ (block 14 g of FIG. 5).

The frequency of update of the equaliser coefficients in the case ofblock equalisation, or the coefficient step size in the case of adaptiveequalisation, can be selected on the basis of an estimate of the degreeof channel non-stationarity or temporal selectivity, e.g. through anestimate of a channel Doppler spread r, (block 14 h of FIG. 5).

The equaliser delay can be selected on the basis of an estimate of thechannel phase characteristics derived from location of the channel zerosin the z-plane γ₄ (block 14 i of FIG. 5).

Reference will now be made to FIG. 6 which is a schematic block diagramillustrating the selection of a particular equalisation algorithm basedon the estimated channel conditions. While the sequence described belowrepresents one useful embodiment of the invention, it will beappreciated that any other sequence can be utilised to implementselection of the appropriate equaliser algorithm.

Level 6 a in FIG. 6 denotes the selection of a linear or non-linearequaliser structure. Linear equalisation based on a transversal filterstructure has been employed since the early work of Lucky (R. W. Lucky,“Automatic Equalization for Digital Communication”, Bell SystemTechnical Journal, vol. 44, pp. 547-588, April 1965), Proakis and Miller(J. G. Proakis and J. H. Miller, “An Adaptive receiver for DigitalSignaling Through Channels with Intersymbol Interference”, IEEETransactions on Information Theory, vol. 15, no. 4, pp. 484-497, July1969) and others (see S. U. H. Qureshi “Adaptive Equalization”,Proceedings of the IEEE, vol. 73, no. 9, pp. 1349-1387, September 1985and references therein). Non-linear equalisers include decision-feedbackequalisers (described for example in J. Salz, “Optimum Mean SquareDecision Feedback Equalization”, Bell System Technical Journal, vol. 52,pp. 1341-1373, October 1073, and C. A. Belfiore and J. H. Park, Jr.,“Decision Feedback Equalization”, Proceedings of the IEEE, vol. 67, no.8, pp. 1143-1156, August 1979) and maximum-likelihood (ML) or maximum aposteriori probability (MAP) trellis equalisers (described for examplein G. D. Forney, Jr., “Maximum Likelihood Sequence Estimation of DigitalSequences in the Presence of Intersymbol Interference”, IEEETransactions on Information Theory, vol. 18, no. 3, pp. 363-378, May1972, and L. R. Bahl, J. Cocke, F. Jelinek, and Raviv, “Optimal Decodingof Linear Codes for Minimizing Symbol Error Rate”, IEEE Transactions onInformation Theory, vol. 20, pp. 284-287, March 1974). Linear andnon-linear equalisers are also discussed in S. Benedetto, E. Biglieri,and V. Castellani, “Digital Transmission Theory”, Englewood Cliffs,N.J., Prentice-Hall, 1987 and D. P. Taylor, G. M. Vitetta, B. D. Hart,and A. Mammela, “Wireless Channel Equalization”, European Transactionson Telecommunications, vol. 9, no. 2, pp. 117-143, March 1998. Acriterion for making the choice between a linear or non-linear equalisercan be based for example on the location of channel zeros in the z-planeγ₄. In addition, this selection could depend on specific transmissionconditions. For instance, in an HSDPA system, the use of a decisionfeedback equaliser (that is, having a non-linear structure) may belimited to a condition where the user is allocated a significantpercentage of the downlink power—which determines the portion of thedownlink signal that can be used for decision feedback without requiringto make decisions on other user's data.

Level 6 b in FIG. 6 denotes the selection of Baud-spaced orfractionally-spaced equaliser structure. Baud-spaced (symbol- orchip-spaced) and fractionally spaced equalisers are described forexample in S. U. H. Qureshi “Adaptive Equalization”, Proceedings of theIEEE, vol. 73, no. 9, pp. 1349-1387, September 1985 and J. R. Treichler,I. Fijalkow, and C. R. Johnson, Jr., “Fractionally Spaced Equalizers”,IEEE Signal Processing Magazine, vol. 13, no. 3, pp. 65-81, May 1996.This selection is made based for instance on the location of the channelzeros in the z-plane γ₄, and could optionally take into account theamount of excess transmission bandwidth (roll-off factor of transmit andreceive filters).

It will be clear that either baud-spaced or fractionally spaced designcan be used with either of the linear or non-linear selections.

Level 6 c in FIG. 6 denotes the selection of the equaliser costfunction, specifically between the options of Minimum Mean-Square Error(MMSE) criterion, Least-Squares (LS) criterion, Zero-Forcing (ZF)criterion, or a criterion based on a different cost, including themaximum-likelihood (ML) criterion and the maximum a posterioriprobability (MAP) criterion. MMSE, LS, ZF and ML equalizers aredescribed in S. U. H. Qureshi “Adaptive Equalization”, Proceedings ofthe IEEE, vol. 73, no. 9, pp. 1349-1387, September 1985 and S.Benedetto, E. Biglieri, and V. Castellani, “Digital TransmissionTheory”, Englewood Cliffs, N.J., Prentice-Hall, 1987, while MAPequalisers are discussed in D. P. Taylor, G. M. Vitetta, B. D. Hart, andA. Mammela, “Wireless Channel Equalization”, European Transactions onTelecommunications, vol. 9, no. 2, pp. 117-143, March 1998 and C. Luschiet al., “Advanced Signal Processing Algorithms for Energy-EfficientWireless Communications”, Proceedings of the IEEE vol. 88, no. 10, pp.1633-1650, October 2000. Parameters that can be used to select betweenthese criteria include an estimate of the signal-to-disturbance ratio orother parameters indicative of the statistical distribution of thedisturbance. For instance, acceptable performance can be obtained forhigh signal-to-disturbance ratios using the ZF criterion. On the otherhand, the use of a LS equaliser is preferable with respect to a MMSEequaliser in the presence of non-Gaussian disturbance.

Level 6 d in FIG. 6 denotes the choice between equaliser blockprocessing or the implementation of a tap adaptation rule. The selectionbetween these two strategies may be made dependent on the degree ofchannel non-stationarity or temporal selectivity, e.g. through anestimate of a channel Doppler spread γ₁.

Block processing is mentioned for example in A. Klein, “Data DetectionAlgorithms Specially Designed for the Downlink of CDMA Mobile RadioSystems”, in Proceedings of IEEE Vehicular Technology Conference, vol.1, Phoenix, Ariz., May 1997, pp. 203-207. An adaptive algorithm ismentioned in K. Hooli, M. Latva-aho and M. Juntti, “PerformanceEvaluation of Adaptive Chip-Level Channel Equalizers in WCDMA Downlink”,in Proceedings of IEEE International Conference on Communications, vol.6, Helsinki, Finland, June 2001, pp. 1974-1979.

1. A method of processing radio signals in a radio receiver, the methodcomprising: receiving digital samples of an incoming radio signal andprocessing those samples in accordance with an equaliser algorithmutilising a set of equaliser parameters to generate an equalised output;estimating at least one parameter of a channel over which the incomingsignal has been transmitted; and selecting at least one of saidequaliser parameters based on at least one of said estimated channelparameters.
 2. A method according to claim 1, wherein one of saidchannel parameters represents the degree of non-stationarity of thechannel.
 3. A method according to claim 2, wherein the channel parameterrepresenting the degree of non-stationarity is a Doppler estimate.
 4. Amethod according to claim 1, wherein one of said estimated channelparameters provides an estimate of the energy of the channel outside apredefined temporal window.
 5. A method according to claim 1, whereinone of said estimated channel parameters provides an estimate of thechannel delay spread.
 6. A method according to claim 5, wherein thechannel parameter representing the channel delay spread is the estimatedroot-mean square channel delay spread.
 7. A method according to claim 1,wherein one of said channel parameters estimates the location of thechannel zeros in the z-plane.
 8. A method according to claim 1, whereinone of said channel parameters is a signal-to-disturbance ratio of theincoming signal.
 9. A method according to claim 1, wherein one of saidchannel parameters is an estimate of the cell geometry or its inverse.10. A method according to claim 8, wherein the channel parametersignal-to-disturbance ratio represents the signal-to-disturbance ratioof channel response estimated in the receiver.
 11. A method according toclaim 1, wherein one of said channel parameters is an estimate of thedegree of non-stationarity of the input disturbance.
 12. A methodaccording to claim 11, wherein the channel parameter representing thedegree of non-stationarity of the input disturbance is an estimate ofthe time interval over which the input disturbance can be consideredapproximately constant.
 13. A method according to claim 2, wherein thenon-stationarity channel parameter is used to select at least one of thefollowing equaliser parameters: memory of a filter for estimating achannel response; frequency of update of the estimated channel response;and frequency of update of the equaliser coefficients or coefficientstep size for adaptive equalisation.
 14. A method according to claim 4,wherein the parameter estimated channel energy outside a predefinedwindow is used to select at least one of the following equaliserparameters: time window for estimating a channel response; number ofequaliser coefficients or equaliser time span; and number of feedforwardand/or feedback equaliser coefficients for decision feedbackequalisation.
 15. A method according to claim 5, wherein the channellength or channel delay spread parameter is used to select at least oneof the following equaliser parameters: time window for estimation of thechannel response; number of equaliser coefficients or equaliser timespan; and number of feedforward and/or feedback equaliser coefficientsfor decision feedback equalisation.
 16. A method according to claim 7,wherein the estimate of the location of the channel zeros is used toselect at least one of the following equaliser parameters: number ofequaliser coefficients or equaliser time span; number of feedforwardand/or feedback equaliser coefficients for decision feedbackequalisation; and equaliser delay parameter.
 17. A method according toclaim 8, wherein the channel parameter signal-to-disturbance ratio isused to select at least one of the following equaliser parameters:threshold parameters for estimated channel tap; time window forestimation of the channel response; memory of the filter for estimationof the channel response.
 18. A method according to claim 9, wherein thechannel parameter cell geometry or its inverse is used to select atleast one of the following equaliser parameters: threshold parametersfor estimated channel tap; time window for estimation of the channelresponse; memory of the filter for estimation of the channel response.19. A method according to claim 11, wherein the time interval over whichthe input disturbance is approximately constant is used to select atleast one of the following equaliser parameters: memory of the filterfor estimation of the input disturbance.
 20. A radio receiver for awireless communication system comprising: channel equalisation meansarranged to receive digital samples of an incoming signal and togenerate an equalised output, said channel equalisation means comprisingmeans for processing said digital samples in accordance with anequaliser algorithm utilising a set of equaliser parameters; means forestimating at least one parameter of a channel over which the signal hasbeen received; and means for selecting at least one of said equaliserparameters based on at least one of said estimated channel parameters.21. A radio receiver according to claim 20, comprising a processor andwherein the channel equalisation means, estimate means and selectingmeans comprise code sequences executable by the processor.
 22. A radioreceiver according to claim 21, comprising a memory holding said codesequences.